BALANCED VARIABLE ADDITION IN LINEAR MODELS
研究了从短回归转向长回归时，长回归的最小二乘估计量可能比短回归的估计量更不一致的条件，并解释了何为“平衡添加”。
Abstract This paper studies what happens when we move from a short regression to a long regression in a setting where both regressions are subject to misspecification. In this setup, the least‐squares estimator in the long regression may have larger inconsistency than the least‐squares estimator in the short regression. We provide a simple interpretation for the comparison of the inconsistencies and study under which conditions the additional regressors in the long regression represent a “balanced addition” to the short regression.